1. Field of the Invention
This invention generally relates to analyzing video content and more specifically to predicting user engagement with the content.
2. Description of the Related Art
The sharing of video content on websites has developed into a worldwide phenomenon, supported by dozens of websites. On average, over 10,000 videos are posted every day, and this number is increasing as the tools and opportunities for capturing video become easier to use and more widespread. Millions of people watch the posted videos.
Operators of video sharing websites have a general desire to improve the experiences of the viewers of the shared videos. For example, the viewer experience can be improved by inserting content such as recommendations for additional videos or other items of interest into the watched video. Determining when to insert such content is a difficult problem because the content, if provided at the wrong times, can be distracting and harm the viewer experience. Accordingly, it is important to identify portions of the video where it might be appropriate to insert content or perform other actions that can improve the viewer experience. However, video content contains very few identifying markers that can be used to differentiate among the different portions of a video.
Thus, while there is a desire to improve the viewer experience, determining how to improve the experience for a given video is difficult. The problem is especially acute when multiplied by the thousands of new videos received every day by video sharing sites.